An ensemble-based approach for precise diabetic retinopathy classification using contour-guided ROI isolation and multi-blur augmentation

Diabetic Retinopathy (DR) is a leading cause of vision loss worldwide, necessitating early and accurate diagnosis for effective treatment. This research proposes a robust ensemble-based approach for DR classification, incorporating advanced data pre-processing and optimization techniques to enhance model performance. The study introduces a contours-based cropping method that isolates the retinal region, minimizing background noise and emphasizing the Region of Interest (ROI). A novel data augmentation strategy combining Gaussian and Bilateral Blurs is employed to simulate real-world imaging conditions, increasing dataset diversity and model resilience. Feature extraction uses pre-trained VGG16 and VGG19 models, which transfer high-level visual knowledge to the DR classification task. Feature selection and dimensionality reduction are achieved through ElasticNet and Principal Component Analysis (PCA), optimizing model interpretability and efficiency. Multiple classifiers, including Gradient Boosting and XGBoost, were evaluated to assess model performance, with the Stacking ensemble achieving the highest accuracy of 94.4%. Hyper parameter tuning using Optuna further refined the model, underscoring the importance of optimization in achieving reliable classification results. The findings highlight the effectiveness of ensemble methods combined with sophisticated pre-processing techniques, presenting a valuable tool for automated DR diagnosis. Future work aims to expand the dataset, explore advanced ensemble techniques, and integrate model interpretability methods to enhance clinical applicability. This research contributes to developing accurate, transparent, and resilient models for DR detection, supporting early diagnosis and improved patient outcomes.

Maternal vaccination decision-making in urban and rural Bengaluru, India: A mixed methods study

Maternal immunization is key to reducing morbidity and mortality among both pregnant women and infants; however, improving maternal vaccination uptake remains a challenge globally. We conducted a mixed methods study using a social ecological model in urban and rural sites in Bengaluru, India, to examine vaccination decision-making and factors influencing vaccination during pregnancy at the individual, interpersonal, organizational, community and policy levels. We conducted semi-structured interviews with pregnant women and new mothers ( n  = 70) and family members ( n  = 11), four focus group discussions with 35 women, and in-depth interviews with healthcare providers (HCPs, n  = 26) and policymakers ( n  = 16). A majority (67%) of women were not included in decisions regarding their own pregnancy-related healthcare, which were typically made by other family members, such as husbands and mothers-in-law. HCPs, including community workers, were most influential in maternal vaccination decision-making, followed by family members. Although national guidelines were the next most important influencer, policymakers tended to underestimate communities’ trust in and reliance on these guidelines. Traditional media are considered more trustworthy and influential than social media. Trust in HCPs and long-standing community use and experience with tetanus vaccines promoted what may be characterized as passive acceptance as they were given as a matter of course at antenatal appointments. Use of a social ecological framework indicates that many influences beyond individual-level factors influence maternal vaccine acceptance in developing settings. Clear government priority and policy along with engagement with families, communities and various types of HCPs are likely to be critical in maximizing acceptance of newer maternal vaccines.

Design and performance analysis of a 4-QAM OFDM Li-Fi system for indoor wireless communication

Light Fidelity technology (Li-Fi) is an emerging wireless communication technology that functions under the visible light spectrum for high-speed data transmission. Normally in a wireless communication system, the transmission is possible via RF waves, but Li-Fi works only in the spectrum of visible light having a frequency range from 380 nm to 780 nm. It uses LED as the light source instead of any other kind of light source like lasers. The need for advanced modulation techniques, such as OFDM and QAM, is to obtain higher efficiency and data rates with the system. The OFDM carries the information data pattern of the transmission into several sub-carriers and requires a smaller number of bandwidths. Same way, it has QAM symbols which, because of the in-phase and quadrature components, transmit data-without ISI or any other distortion in a much higher dissimilar time. Thus, the combination of OFDM with QAM improves the integrity of the signal and reduces distortion in the signal. This is a paper that deals fundamentally with the theory of an OFDM-QAM system for Li-Fi applications, its structure, mathematical modelling, performance metrics and larger implications in improving the data transmission efficiency and mitigating the signal distortion for faster speeds, secure and reliable wireless communication in several environments.

Development and electrochemical investigation of Selexipag zinc nanoparticles for controlled drug release

Metal nanoparticles are used in drug delivery to target drugs to specific cells, such as vascular endothelial cells of the pulmonary artery. Among the metal nanoparticles, zinc nanoparticles plays prominent role in sustained and targeted oriented drug delivery system. This study provides a comprehensive analysis of Selexipag zinc nanoparticles (SLX-ZnNP) including their analytical characterization, in vitro drug release behavior, and electrochemical properties. The nanoparticles were prepared by using the controlled sonochemical method to control their size and morphology. UV-Visible, XRD, SEM, and EDX, were employed to evaluate the physicochemical properties, crystalline structure, and surface morphology of the prepared nanoparticles. SLX-ZnNP showed the characteristic UV absorption peaks of at 202.7 and 271.4 nm. The SEM images of SLX-ZnNP particles shown floccule like structure in the images. Additionally, the electrochemical properties of SLX-ZnNP were analyzed by using cyclic voltammetry (CV) to understand their redox behavior and electroactive characteristics. In vitro drug release studies were performed using a dialysis membrane to assess the controlled release profile of SLX-ZnNP. The free SLX drug released rapidly within 8 hours, reaching 80% release. In contrast, the SLX-ZnNP exhibited a controlled release, with 99.72% of the drug being released after 24 hours. Mathematical models were applied to analyze the release profiles and gain insights into the mechanisms governing drug release from the nanoparticles. To ascertain whether the prepared SLX-ZnNP could bind with DNA, we carried out in vitro DNA binding studies and found the intrinsic binding constant (Kb) value to be 7350.26 L/µg. In conclusion, the controlled sonochemical synthesis and comprehensive analysis of SLX-ZnNP highlight their potential for targeted drug delivery in pulmonary arterial hypertension.

Robust tracking of discrete-time linear switched systems with disturbance via second-order ILC with data loss

The purpose of this article is to investigate the second-order P-type iterative learning control (ILC) scheme in the presence of data loss for a class of linear discrete-time switched systems with disturbances. Employing the super-vector representation technique, the discrete-time linear switched system is reformulated as an input-output transmission equation. The robustness of the resulting switched system driven by a second-order P-type ILC scheme is guaranteed through the use of the super-vector representation technique. Importantly, the article also explores cases of data loss occurring during data transmission. The proposed methodology exhibits significantly improved convergence performance compared to the P-type ILC scheme (Yang et al., 2022, Robust finite-iteration tracking of discrete-time systems in repetitive process setting via ILC scheme. International Journal of Robust and Nonlinear Control, 32 (5), 2585–2602. https://doi.org/10.1002/rnc.5782 ). Simulation examples are provided to demonstrate the effectiveness of the proposed scheme.

Students’ perception of authentic assessment in higher education: Exploring the relationship between assessment preference and motivation in higher education

There is an increasing shift from traditional knowledge-testing exams to more effective learning-oriented assessments in Higher Education. There is limited evidence examining students’ perception of the authenticity of different Higher Education assessments predicted by intrinsic, extrinsic, and amotivation levels. Ninety-six young adults (19-49 years; 68 females) completed an online survey to investigate the role of motivation in preference ratings for 25 different assessments. Results showed that students only had a slight preference for certain assessments. In more detail, they had a significantly higher preference for poster submission predicted via intrinsic motivation, poster presentation predicted via intrinsic (to know) and extrinsic (introjected) motivation, multiple choice question exam (within a set framework), predicted via extrinsic (identified and introjected) motivation and amotivation, essay exam predicted via amotivation, and lab report predicted via extrinsic (introjected) motivation and amotivation. Therefore, alongside the facilitation of knowledge and understanding, assessments in Higher Education should be designed to foster interest and passion to conceptual learn and enjoy the content.

Influence of tool positions variation on axial force, torque sensitivity, mechanical and microstructure properties of Al/Cu dissimilar FSW

Study on tool offset must be necessary to minimise IMCs formation and mechanical properties enhancement. Tool offset has a significant variations in the instantaneous force and torque are measures for the welding process. Increasing in the offset means more % of Al. This means softer IMCs formation and so increasing in offset distance decrease on load in the spindle/Z-axis and X-axis torque. A precise critical offset towards Al plate could result in a defect-free joint and superior mechanical performance. 1.5 mm offset gives smooth variations in the peaks, indicating a uniform distribution of the intermetallic compound, smooth weld surface and defect-free weld leads to better mechanical properties. In comparison to the Al base metal, the weld sample had more tensile and yield strength of 95% and 100%, respectively in case of optimised offset of 1.5 mm. 1.5 mm offset give maximum compressive strength (97.5% of the Al BM), maximum tensile properties and micro-hardness (176.2HV) due to fine grain with Al 44 μm and Cu 42 μm. As the grain size decreases so it helps to increase tensile properties and the strength of the joint depends on the offset distance and formation of the suitable amount of the intermetallics.

Quantification and spatial assessment of industrial Cd and Pb emission across India

Heavy metals, particularly cadmium (Cd) and lead (Pb), pose a significant environmental challenge worldwide owing to their detrimental effects on ecosystem sustainability. India, the most populous country in the world, presently faces severe contamination by heavy metals. This study identifies and quantifies the Cd and Pb emissions from the principal industrial sources at the district level across India, using the IPCC bottom-up approach for 2019. The developed emission inventory includes various industries, notably coal-based power plants, captive power plants, cement production, iron and steel manufacturing, non-ferrous metal production, municipal and biomedical waste incineration, the glass industry, and fly ash generated. Annual emissions were reported to be approximately 2,016 tonnes/year (t/yr) for Cd and 19,258 t/yr for Pb, where coal combustion across different industries emitted approximately 93 t of Cd and 927 t of Pb, with the energy sector contributing about 66% and fly ash accounting for over 80% of total emissions. Among non-ferrous metals, copper production is solely responsible for 44 t and 77 t of Cd and Pb, respectively. The research also identifies regional hotspots for Cd and Pb emissions across India, highlighting areas where targeted remediation strategies can support sustainable environmental management.

Emerging Crisis: Rise of HIV Through Injectable Drugs Use in Adolescents as a New Pandemic in Tripura, India

Human Immunodeficiency Virus (HIV) is primarily transmitted through blood, shared injecting equipment, and sexual fluids. In Tripura, India, the rising spread of HIV, particularly among adolescents, is a major public health issue. This mini-review highlights the increase in HIV cases, largely driven by injecting drug use (IDU) and needle sharing, especially among younger individuals. Since the first case in 1996, the number of infections have surged, with injectable drugs like heroin and methamphetamines being the main transmission route. A lack of awareness and prevention measures exacerbates the problem. The review also touches on HIV-1 morphology, focusing on its structure and replication. Given the rising HIV/acquired immunodeficiency syndrome (AIDS) rates from 2015 to 2023, urgent action is required. Prevention strategies should involve schools, non-governmental organisations (NGOs), and health authorities to promote awareness, safe practices, and access to anti-retroviral treatments to curb the spread among adolescents.

Multimuons in cosmic-ray events as seen in ALICE at the LHC